Variational Bayesian Inference Toolbox
This module is inspired by the paper ‘Black Box Variational Inference’ by Rajesh Ranganath et al. It attempts to make nearly trivial the task of fitting a variational distribution to a user-specified log-likelihood function without derivatives. Currently it only uses a mean field variational distribution, but the main class VariationalInferenceMF is flexible enough for simple subclassing in the future. This module also contains a number of implementations of stochastic gradient descent algorithms to be used for optimization.
Release files for varibayes 0.0.1
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
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| varibayes-0.0.1-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Release files / varibayes-0.0.1-py2.py3-none-any.whl
| Download URL | varibayes-0.0.1-py2.py3-none-any.whl |
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| Size | 8.0 kB |
| Tags | Python 2 Python 3 |
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